Identifying Potential miRNA Biomarkers for Gastric Cancer Diagnosis Using Machine Learning Variable Selection Approach

Aim: This study aimed to accurately identification of potential miRNAs for gastric cancer (GC) diagnosis at the early stages of the disease. Methods: We used GSE106817 data with 2,566 miRNAs to train the machine learning models. We used the Boruta machine learning variable selection approach to iden...

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Detalles Bibliográficos
Autores principales: Gilani, Neda, Arabi Belaghi, Reza, Aftabi, Younes, Faramarzi, Elnaz, Edgünlü, Tuba, Somi, Mohammad Hossein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Genetics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785967/
https://www.ncbi.nlm.nih.gov/pubmed/35082831
http://dx.doi.org/10.3389/fgene.2021.779455

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8785967/
https://www.ncbi.nlm.nih.gov/pubmed/35082831
http://dx.doi.org/10.3389/fgene.2021.779455

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